Looker Adds Support for Presto, Spark SQL

With support for Presto, Spark SQL and new data stores, Looker unlocks further value in Apache Hadoop by putting data in the hands of decision-makers.

Apache Hadoop

Looker, which provides a data exploration and business intelligence platform for businesses, today announced support for Presto and Spark SQL as well as updates to its support for Impala and Hive.

Looker enables enterprises to describe, define and analyze the data where it lives, which cuts down on the time, expertise and cost of moving the data. With its latest offering, Looker expands its list of supported data warehouses, such as Amazon Redshift, and ensures compatibility with the Amazon Elastic MapReduce (Amazon EMR) suite of frameworks.

"To make meaningful business decisions, all individuals within an organization must have easy access to tools for performing business analytics with Hadoop," said Anurag Gupta, vice president of Database Services at Amazon Web Services, in a statement. "Looker's support of Presto and Spark SQL helps AWS customers access all their organizational data, whether in Amazon Relational Database Service (Amazon RDS), Amazon Redshift, or, with today's announcement, in an Amazon Simple Storage Service (Amazon S3) data lake accessed through one of the many SQL engines supported by Amazon EMR."

Presto is an Apache-licensed, open-source SQL query engine optimized for high-speed interactive analytics at scale. Spark SQL is Apache Spark's module for working with structured data. Apache Hive is a data warehouse infrastructure built on top of Hadoop for providing data summarization, query and analysis. Impala, developed by Cloudera, is an Apache incubator project for a modern, open-source, distributed SQL query engine for Apache Hadoop.

"With Looker on Hadoop, data analysts can create a single source of truth for the entire enterprise, so every business team can quickly ask and answer their own questions," said Frank Bien, CEO at Looker, in a statement. "Now all decision-makers, not just a handful of data scientists, can utilize the valuable data in Hadoop to drive better business decisions."

Bien said it's been typically painfully slow to do data analysis in Hadoop. Typically, data analysts had to move subsets of data into data warehouses to perform analysis and, as a result, business teams rarely had direct access. Yet, thanks to advances in SQL query engines, big data technologies are finally accessible for business analytics and the vision of Hadoop as more than a data store is now a reality. Data analysts can now build a data model across all their data in Hadoop or other databases, easily transform raw data into meaningful metrics and allow business teams to utilize years of stored data in Hadoop.

"Looker makes the data in Hadoop easy for everyone to access and explore in a single platform. With Looker, we can see and respond to the impact of product changes immediately, greatly improving our customer experience," said Mike Van Kempen, senior business analyst at Acorns.

In a blog post, Bien said as innovative as Hadoop was for storing data, the Hadoop ecosystem was not ready to do business analytics—meaning fast, interactive business analysis and exploration of enormous quantities of data. He noted that vendors that jumped in early had to build complicated systems that transformed, moved, cubed and generally "messed" with the data in Hadoop.

Bien argues that even after all that, none of the solutions allowed for the speed and repeatability that's necessary for business analytics to be truly valuable.

However, "Today we announced that with the improvements in the speed and performance of connectors like Spark SQL and Presto, updates on Impala and Hive, we have customers like Acorns and Yahoo doing their business analytics directly on Hadoop," he said in his post. "Actionable, reliable analytics over all the data in their massive data stores—not just a sub-set."

Last month, Looker announced it closed a $48 million Series C funding round led by Kleiner Perkins Caufield & Byers (KPCB), with participation from previous investors Redpoint Ventures, Meritech and Sapphire Ventures.

The financing will be used to accelerate the company's growth through investments in sales, marketing and engineering as well as to fuel further international expansion. Including the recent round, Looker has raised a total of $96 million since its launch in 2013.